CRMs can help you identify deviations and stay on track, using machine learning.

Every business report is made up of a rollercoaster of trends. Your sales, marketing, or revenue numbers will rarely ever be consistent across the board; highs and lows are a part of the business. If you managed to close X deals last month, hoping to close more than X deals is ambitious yet idealistic while hoping to close somewhere around N deals is persistent and realistic. You, as a company, should attempt to set expectations that strike the balance between the two.

As long as a metric performs closely above or below the median average, we call it normal, because that pattern is permissible and natural. However, roller coasters have a fixed high and low point, beyond which a ride cannot go. Likewise, companies need to define how high a metric can go and how low a metric can get — the points beyond which any rise or drop will be considered an anomaly.

What’s an anomaly?

An anomaly is any deviation from what’s considered normal, expected, or standard. When 600 of the emails you sent last night bounced, and the bounce rate for the last few emails you’ve sent is between 163 and 319, that’s an anomaly; the difference is too large to be permissible.

An anomaly doesn’t necessarily have to be bad, either. If your ROI for a particular AdWord is exceedingly high this month compared to what you gained in the previous month, that’s an anomaly, too.

When an anomaly occurs, you’ll see your graph suddenly skew in one direction, standing out from the current trend. It’s important that businesses identify these anomalies and probe their causes and effects, in order to prevent or recreate them in the future.

Anomalies in CRM

Almost every modern business uses a CRM to manage their everyday sales activities. CRM is an ever-growing, sophisticated repository of huge volumes of data, which can invite anomalies on a fairly regular basis. If your company uses reports to analyze, review, and improve the individual performance of employees, products, services, campaigns, and ads, you’ve certainly come across anomalies by now.

However, how often do you see an anomaly coming beforehand? Scratch that — how often do you see them as they happen? One of the major hurdles that businesses with an outdated CRMs face is the lack of a dedicated functionality to help them deal with anomalies. Manual identification of anomalies could cost you hours of productivity and sets you back in your race to control it. When your plan isn’t working as you intend it to, you must steer it back on track, before things get out of hand.

Artificial intelligence holds the key

Artificial intelligence is making strides in the world of technology, helping businesses solve complex problems and automate mundane, laborious tasks. AI-based solutions are rapidly being incorporated by industries and CRM vendors are no strangers to this trend. Among the plethora of opportunities that AI offers, anomaly detection is quite the proposition. How great would it be if your CRM was smart enough to help you stay one step ahead at handling anomalies?

Machine learning is the art of teaching a machine to do a task without any human intervention, through observation, analysis, and practice. When you provide sufficient historical data, training, and regression, your CRM can learn about anomalies and detect them for you, saving your time, resources, and reputation — just like that. Over time, the detection algorithm gets more accurate through trial and error, making AI an increasingly efficient alternative for manual detection.

Predictive AI to stay proactive

AI presents you with an endless list of possibilities to solve problems. When you can teach software to detect anomalies as they happen, why not teach it to predict them before they happen? That’s what powerful CRMs such as Zoho CRM offer — an intelligent prediction tool that creates a comprehensive study of your historical trends, to make informed predictions on future trends.

Predictive AI allows you to make proactive decisions that help control upcoming anomalies, potentially minimizing or capitalizing on them at the right time. If you foresee a drop in lead conversion, you can quickly come up with a catalyst to boost your numbers before the anomaly even occurs. Hence, predictive AI allows you to prepare in advance to tackle anomalies, helping you to always tread with the trend.

How does AI do it?

Artificial intelligence requires robust data to work with. When you populate your CRM with quality, comprehensive data, your AI can make predictions from the go. Although every AI is nurtured with an extensive set of training data before it’s deployed, it’s your in-house data that personalizes the knowledge base of the AI for you. Once the AI has access to your company’s historical trends, such as lead conversion, task closure, and calls dropped, it can make fairly accurate predictions of where those trends are heading next.

Every anomaly has certain attributes, some of which are more common than others. Now, whenever the AI detects a scenario which closely resembles an anomaly, they’ll be marked as a potential anomaly, too. Over time, this prediction gets more accurate through trial and error.

Intelligent Assistants

Detecting anomalies when they occur and predicting them before they occur are a tremendous feat of AI, but what good are they if you don’t hear about them in time? That’s why it’s important to have an AI-based digital assistant that can alert you whenever an anomaly comes into the picture.

Zia, coupled with Zoho CRM, is one such intelligent assistant that can help you stay up to date on any anomalies creeping into your business process. This can come handy for mobile users who are on the run, to be instantly notified about pressing deviations. As you can see, when the entire process of detection, prediction, and notification is automated by an intelligent assistant, businesses can freely focus on finding ways to control anomalies, instead of wasting their resources on finding them.

Adopt an AI-rich CRM today!

If several sales calls were dropped this month, when would you want to find out about them? In the monthly sales report or when the drops were happening, in real time? Here’s a better choice — how about a week before they happened? Artificial intelligence is not the next big thing because it already is. AI can do a lot more than detect anomalies; they can be an all-around assistant for your business activities. Zoho CRM, for your consideration.